Lack of spacing effects during piano learning
Bibliographic record
Abstract
Spacing effects during retention of verbal information are easily obtained, and the effect size is large. Relatively little evidence exists on whether motor skill retention benefits from distributed practice, with even less evidence on complex motor skills. We taught a 17-note musical sequence on a piano to individuals without prior formal training. There were five lags between learning episodes: 0-, 1-, 5-, 10-, and 15-min. After a 5-min retention interval, participants' performance was measured using three criteria: accuracy of note playing, consistency in pressure applied to the keys, and consistency in timing. No spacing effect was found, suggesting that the effect may not always be demonstrable for complex motor skills or non-verbal abilities (timing and motor skills). Additionally, we taught short phrases from five songs, using the same set of lags and retention interval, and did not find any spacing effect for accuracy of song reproduction. Our findings indicate that although the spacing effect is one of the most robust phenomena in the memory literature (as demonstrated by verbal learning studies), the effect may vary when considered in the novel realm of complex motor skills such as piano performance.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".